| Pruning deep neural networks from a sparsity perspective E Diao, G Wang, J Zhan, Y Yang, J Ding, V Tarokh arXiv preprint arXiv:2302.05601, 2023 | 13 | 2023 |
| Understanding backdoor attacks through the adaptability hypothesis X Xian, G Wang, J Srinivasa, A Kundu, X Bi, M Hong, J Ding International Conference on Machine Learning, 37952-37976, 2023 | 6 | 2023 |
| A theoretical understanding of neural network compression from sparse linear approximation W Yang, G Wang, J Ding, Y Yang arXiv preprint arXiv:2206.05604, 2022 | 3 | 2022 |
| A unified detection framework for inference-stage backdoor defenses X Xian, G Wang, J Srinivasa, A Kundu, X Bi, M Hong, J Ding Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Mitigating group bias in federated learning: Beyond local fairness G Wang, A Payani, M Lee, R Kompella arXiv preprint arXiv:2305.09931, 2023 | 1 | 2023 |
| Subset privacy: Draw from an obfuscated urn G Wang, J Ding arXiv preprint arXiv:2107.02013, 2021 | 1 | 2021 |
| Demystifying Poisoning Backdoor Attacks from a Statistical Perspective X Xian, G Wang, J Srinivasa, A Kundu, X Bi, M Hong, J Ding arXiv preprint arXiv:2310.10780, 2023 | | 2023 |
| Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization G Li, G Wang, J Ding IEEE Transactions on Information Theory, 2023 | | 2023 |
Jie DingAssociate Professor, University of Minnesota Twin CitiesVerified email at umn.edu
